{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T08:13:01.220935Z",
     "iopub.status.busy": "2025-09-28T08:13:01.220667Z",
     "iopub.status.idle": "2025-09-28T08:13:04.997485Z",
     "shell.execute_reply": "2025-09-28T08:13:04.996782Z"
    },
    "jupyter": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "from river.datasets import ImageSegments\n",
    "from river.preprocessing import MinMaxScaler\n",
    "from river.tree import HoeffdingTreeClassifier\n",
    "from deep_river.classification import Classifier\n",
    "from torch import nn\n",
    "from tqdm import tqdm\n",
    "import matplotlib.pyplot as plt\n",
    "import torch\n",
    "import numpy as np\n",
    "import random\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.utils import resample\n",
    "from sklearn.manifold import TSNE\n",
    "\n",
    "random.seed(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create Stream"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T08:13:05.000389Z",
     "iopub.status.busy": "2025-09-28T08:13:05.000082Z",
     "iopub.status.idle": "2025-09-28T08:13:05.129507Z",
     "shell.execute_reply": "2025-09-28T08:13:05.128602Z"
    }
   },
   "outputs": [],
   "source": [
    "stream_size = 10_000\n",
    "\n",
    "x, y = list(zip(*ImageSegments()))\n",
    "x = np.array(x)\n",
    "y = np.array(y)\n",
    "\n",
    "# Divide classes into two task specific sets\n",
    "task_classes = [\n",
    "    [\"brickface\", \"window\", \"cement\"],\n",
    "    [\"sky\", \"foliage\", \"path\", \"grass\"],\n",
    "]\n",
    "\n",
    "# Divide all samples into their specific tasks\n",
    "data_train = []\n",
    "data_test = []\n",
    "for classes_t in task_classes:\n",
    "    x_t = np.concatenate([x[y == c] for c in classes_t])\n",
    "    y_t = np.concatenate([330 * [c] for c in classes_t])\n",
    "    x_train, x_test, y_train, y_test = train_test_split(\n",
    "        x_t, y_t, test_size=0.25, stratify=y_t\n",
    "    )\n",
    "    x_train, y_train = resample(\n",
    "        x_train, y_train, n_samples=int(stream_size / 2), stratify=y_train\n",
    "    )\n",
    "    data_train.append(list(zip(x_train, y_train)))\n",
    "    data_test.append(list(zip(x_test, y_test)))\n",
    "\n",
    "data_train = data_train[0] + data_train[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T08:13:05.133134Z",
     "iopub.status.busy": "2025-09-28T08:13:05.132844Z",
     "iopub.status.idle": "2025-09-28T08:13:09.412721Z",
     "shell.execute_reply": "2025-09-28T08:13:09.411717Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/cedrickulbach/Documents/Projects/deep-river/.venv/lib/python3.10/site-packages/threadpoolctl.py:1226: RuntimeWarning: \n",
      "Found Intel OpenMP ('libiomp') and LLVM OpenMP ('libomp') loaded at\n",
      "the same time. Both libraries are known to be incompatible and this\n",
      "can cause random crashes or deadlocks on Linux when loaded in the\n",
      "same Python program.\n",
      "Using threadpoolctl may cause crashes or deadlocks. For more\n",
      "information and possible workarounds, please see\n",
      "    https://github.com/joblib/threadpoolctl/blob/master/multiple_openmp.md\n",
      "\n",
      "  warnings.warn(msg, RuntimeWarning)\n"
     ]
    }
   ],
   "source": [
    "classnames = task_classes[0] + task_classes[1]\n",
    "tsne = TSNE(init=\"pca\", learning_rate=\"auto\", n_jobs=-1)\n",
    "x_array = np.array([list(x_i.values()) for x_i in x])\n",
    "x_viz = tsne.fit_transform(x_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T08:13:09.416209Z",
     "iopub.status.busy": "2025-09-28T08:13:09.415943Z",
     "iopub.status.idle": "2025-09-28T08:13:09.711359Z",
     "shell.execute_reply": "2025-09-28T08:13:09.710674Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x12a0473a0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "cm = [\n",
    "    \"goldenrod\",\n",
    "    \"gold\",\n",
    "    \"yellow\",\n",
    "    \"aquamarine\",\n",
    "    \"seagreen\",\n",
    "    \"limegreen\",\n",
    "    \"lawngreen\",\n",
    "]\n",
    "for c_idx, x_c in enumerate([x_viz[y == c] for c in classnames]):\n",
    "    scatter = ax.scatter(\n",
    "        x_c[:, 0],\n",
    "        x_c[:, 1],\n",
    "        c=len(x_c) * [cm[c_idx]],\n",
    "        s=3,\n",
    "        alpha=0.8,\n",
    "        label=classnames[c_idx],\n",
    "    )\n",
    "\n",
    "ax.legend(loc=(1.04, 0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define evaluation procedure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T08:13:09.713896Z",
     "iopub.status.busy": "2025-09-28T08:13:09.713689Z",
     "iopub.status.idle": "2025-09-28T08:13:09.719495Z",
     "shell.execute_reply": "2025-09-28T08:13:09.718891Z"
    }
   },
   "outputs": [],
   "source": [
    "# Define function to calculate accuracy on testing data for each task\n",
    "def get_test_accuracy(model, data_test):\n",
    "    results = []\n",
    "    for data_test_i in data_test:\n",
    "        ys = []\n",
    "        y_preds = []\n",
    "        for x_test, y_test in data_test_i:\n",
    "            ys.append(y_test)\n",
    "            y_preds.append(model.predict_one(x_test))\n",
    "        accuracy = accuracy_score(ys, y_preds)\n",
    "        results.append(accuracy)\n",
    "    return results\n",
    "\n",
    "\n",
    "# Define training and testing loop\n",
    "def eval_separate_testing(model, data_train, data_test):\n",
    "    scaler = MinMaxScaler()\n",
    "    step = 0\n",
    "    steps = []\n",
    "    results = [[] for task in data_test]\n",
    "    for x, y in tqdm(data_train):\n",
    "        step += 1\n",
    "        scaler.learn_one(x)\n",
    "        x = scaler.transform_one(x)\n",
    "        model.learn_one(x, y)\n",
    "\n",
    "        if step % 100 == 0:\n",
    "            test_accuracies = get_test_accuracy(model, data_test)\n",
    "            for idx, accuracy in enumerate(test_accuracies):\n",
    "                results[idx].append(accuracy)\n",
    "            steps.append(step)\n",
    "    return steps, results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluate Classifiers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T08:13:09.721785Z",
     "iopub.status.busy": "2025-09-28T08:13:09.721562Z",
     "iopub.status.idle": "2025-09-28T08:13:24.211020Z",
     "shell.execute_reply": "2025-09-28T08:13:24.210156Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
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      "\r",
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      "\r",
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      "\n"
     ]
    }
   ],
   "source": [
    "# Evaluate a simple MLP classifier\n",
    "class SimpleMLP(nn.Module):\n",
    "    def __init__(self, n_features):\n",
    "        super(SimpleMLP, self).__init__()\n",
    "        self.dense0 = nn.Linear(n_features, 5)\n",
    "        self.nonlin = nn.ReLU()\n",
    "        self.dense1 = nn.Linear(5, 2)\n",
    "        self.softmax = nn.Softmax(dim=-1)\n",
    "\n",
    "    def forward(self, X, **kwargs):\n",
    "        X = self.nonlin(self.dense0(X))\n",
    "        X = self.nonlin(self.dense1(X))\n",
    "        X = self.softmax(X)\n",
    "        return X\n",
    "\n",
    "\n",
    "mlp = Classifier(\n",
    "    SimpleMLP(30),\n",
    "    loss_fn=\"binary_cross_entropy_with_logits\",\n",
    "    optimizer_fn=\"sgd\",\n",
    "    lr=0.05,\n",
    "    seed=42,\n",
    ")\n",
    "steps, results_mlp = eval_separate_testing(mlp, data_train, data_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T08:13:24.214081Z",
     "iopub.status.busy": "2025-09-28T08:13:24.213597Z",
     "iopub.status.idle": "2025-09-28T08:13:34.791460Z",
     "shell.execute_reply": "2025-09-28T08:13:34.790853Z"
    }
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      " 89%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                              | 8900/10000 [00:09<00:01, 695.61it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 90%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                           | 9000/10000 [00:09<00:01, 699.90it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 91%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                        | 9100/10000 [00:09<00:01, 703.52it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 92%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                     | 9200/10000 [00:09<00:01, 701.34it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 93%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                   | 9300/10000 [00:09<00:00, 708.38it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 94%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                | 9400/10000 [00:09<00:00, 706.90it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 95%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎             | 9500/10000 [00:09<00:00, 702.33it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 96%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████           | 9600/10000 [00:10<00:00, 697.37it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 97%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊        | 9700/10000 [00:10<00:00, 703.23it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 98%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌     | 9800/10000 [00:10<00:00, 699.77it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 99%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎  | 9900/10000 [00:10<00:00, 706.80it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10000/10000 [00:10<00:00, 705.44it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10000/10000 [00:10<00:00, 945.89it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# Evaluate a Hoeffding Tree classifier\n",
    "tree = HoeffdingTreeClassifier(tau=0.05)\n",
    "steps, results_tree = eval_separate_testing(tree, data_train, data_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize Accuracy over Timesteps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T08:13:34.794150Z",
     "iopub.status.busy": "2025-09-28T08:13:34.793821Z",
     "iopub.status.idle": "2025-09-28T08:13:35.068270Z",
     "shell.execute_reply": "2025-09-28T08:13:35.067649Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x12c439a50>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(nrows=2, figsize=(6, 6), sharex=True)\n",
    "results = {\"MLP\": results_mlp, \"Hoeffding Tree\": results_tree}\n",
    "for model_idx, (model_name, model_results) in enumerate(results.items()):\n",
    "    ax = axs[model_idx]\n",
    "    ax.plot(steps, model_results[0], label=\"Task 1\")\n",
    "    ax.plot(steps, model_results[1], label=\"Task 2\")\n",
    "    ax.axvline(5000, c=\"red\", label=\"Change of Training Task\")\n",
    "    ax.set_ylabel(\"Accuracy\")\n",
    "    ax.set_title(model_name)\n",
    "axs[-1].set_xlabel(\"Steps\")\n",
    "axs[-1].set_xlim(0, 10000)\n",
    "axs[0].legend(loc=(1.04, 0))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.11"
  },
  "vscode": {
   "interpreter": {
    "hash": "588c5aed37ac83ab820db8800694f2ee474f3b87874329a77c5b9c85c1eac9fa"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
